Top Microsoft Software Engineer Interview Questions 2026

Two approaches: (1) in-order traversal must produce strictly increasing values — track previous node and compare. (2) Recursive with min/max bounds — each node must satisfy min < node.val < max; recurse with updated bounds. The bounds approach avoids tracking a previous pointer and works for iterative DFS too.

Chat: WebSocket connections per user, channels as pub/sub topics. Persistence in Azure Cosmos DB (multi-region writes for global presence). Video: WebRTC for P2P; SFU (Selective Forwarding Unit) for group calls, TURN/STUN for NAT traversal. Presence service for online status. End-to-end notification fanout via Service Bus. Eventual consistency for read replicas; strong consistency for message ordering within a channel.

Be specific — generic answers fail. Pick a product line (Azure, GitHub, VS Code, Xbox, M365) and explain why its trajectory or technical problems excite you. Mention growth mindset culture and the mission: "empower every person and organization on the planet to achieve more." Tie to your own experience: a Microsoft product you ship with, an open-source contribution, a use-case you care about.

Maintain an auxiliary min-stack alongside the main stack. On push: push to main; push min(new value, current min) to min-stack. On pop: pop both. getMin() = top of min-stack. All operations O(1). Space-optimized variant: only push to min-stack when the new value is ≤ current min, and pop conditionally.

Object store with three storage tiers (hot, cool, archive) — lifecycle policies move blobs across tiers. Consistent hashing for blob placement. Geo-replication (GRS, ZRS) for durability. Metadata service separate from data plane. SAS tokens (signed URLs) for delegated access with scoped permissions. Versioning + soft-delete for safety. Strong read-after-write consistency for new uploads.

Iterative: maintain prev = null, curr = head. While curr: save next, curr.next = prev, prev = curr, curr = next. Return prev. O(n) time, O(1) space. Recursive variant is elegant but O(n) stack. Be ready for the follow-up: reverse in groups of K.

Source trigger (webhook on push/PR) → orchestrator schedules build on agent pool (Linux/Windows/Mac). Build artifacts pushed to artifact store. Test runner stage (unit, integration, e2e in parallel). Deployment stages with manual gates and approvals (dev → staging → prod). Rollback automation on failed health check. Audit log for compliance. Pipeline-as-code (YAML) for versioning.

BFS with a queue. Track level boundary by recording the queue size at the start of each level — pop exactly that many nodes into a sub-list. Push their children for the next level. O(n) time, O(w) space where w is max width.

Growth-mindset signal — central to Microsoft culture. Pick a concrete mistake with real impact. Own it without deflecting. Describe what specifically changed in your behavior or process afterward — a checklist, a review you instituted, a new habit. Close with a measurable improvement that demonstrates the lesson stuck.

Backtracking. Sort candidates to enable pruning. Recurse with (start_index, remaining, path). At each step try each candidate from start_index onward (allows reuse); if remaining < 0 prune; if remaining == 0 record path; else recurse with remaining - candidate. Sort lets you break early when candidate > remaining.

Vector clocks per file (or per chunk) to detect concurrent modifications. Default policy: last-write-wins for non-conflicting paths. For true conflicts, prompt user with both versions (rename one as "filename (conflict).ext"). Delta sync — only ship changed chunks (rolling hash like rsync). Conflict detection runs at chunk boundary, not whole file. Audit log for restoration.

Two passes. First pass: build frequency map of all characters. Second pass: iterate the string and return the first char whose count is 1. O(n) time, O(k) space where k is alphabet size. LinkedHashMap variant in Java preserves insertion order for one-pass elegance.

In-place. Step 1: transpose the matrix (swap matrix[i][j] with matrix[j][i] for i < j). Step 2: reverse each row. Result is a 90-degree clockwise rotation. O(n²) time, O(1) space. For 90 counter-clockwise: transpose then reverse columns.

Crawler: distributed BFS with politeness rules (robots.txt, rate limits). Indexer: parses pages, builds inverted index (term → doc IDs + positions), shards by term hash. Ranking: TF-IDF for retrieval, PageRank for authority, plus learning-to-rank ML layer. Query path: parse → fan-out to index shards → merge top-K → re-rank → render. Separate read/write paths; caching for hot queries.

Cross-team alignment story. Show how you built a coalition — used data, prototypes, 1:1 conversations to surface a shared problem. Avoided escalation as the first lever. Recorded the outcome in a doc/wiki to make it durable. End with a measurable team-level result, not "people agreed with me."

Greedy O(n). Track the farthest reachable index. Iterate i from 0 to n-1: if i > farthest, return false (stuck). Otherwise farthest = max(farthest, i + nums[i]). If farthest ≥ n-1, return true. Avoids DP's O(n²) overhead.

SMTP for inbound/outbound delivery; IMAP/MAPI for client sync. Sharded mailbox storage (by user ID hash) for write isolation. Full-text search via Elasticsearch (per-user index for permissions). Mobile push via APNS/FCM with batched delivery. Spam/phishing pipeline in front of mailbox write. Calendar+contacts as separate services sharing user identity. Multi-region replication for HA.

Combine ownership with growth mindset. Describe the project, your contribution, the impact (numbers). Then articulate the technical or process decision you'd revisit — not a regret about the team, but about your own judgment. Show what you've internalized for your next project.